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        "<a href=\"https://colab.research.google.com/github/Farmhouse121/Adventures-in-Financial-Data-Science/blob/main/Find_Correlated_Stocks_for_the_NASDAQ_100.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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        "print(\"Installing yfinance and getting data...\")\n",
        "!pip install yfinance 1>/dev/null\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from yfinance import download\n",
        "from datetime import datetime\n",
        "\n",
        "# set time frame of analysis\n",
        "today=datetime.now()\n",
        "start_year=today.year-3\n",
        "\n",
        "# this list as of 2020-12-21 https://www.nasdaq.com/press-release/annual-changes-to-the-nasdaq-100-index-2020-12-11\n",
        "# you must use Adjusted Close to account for distributions such as dividends and splits, not simple Close \n",
        "prices=download(['AAPL','ADBE','ADI','ADP','ADSK','AEP','ALGN','AMAT','AMD','AMGN','AMZN','ANSS','ASML','ATVI','AVGO','BIDU','BIIB','BKNG','CDNS','CDW','CERN','CHKP','CHTR',\n",
        "                 'CMCSA','COST','CPRT','CRWD','CSCO','CSX','CTAS','CTSH','DLTR','DOCU','DXCM','EA','EBAY','EXC','FAST','FB','FISV','FOXA','GILD','GOOG','GOOGL','HON','IDXX',\n",
        "                 'ILMN','INCY','INTC','INTU','ISRG','JD','KDP','KHC','KLAC','LRCX','LULU','MAR','MCHP','MDLZ','MELI','MNST','MRNA','MRVL','MSFT','MTCH','MU','NFLX','NTES',\n",
        "                 'NVDA','NXPI','OKTA','ORLY','PAYX','PCAR','PDD','PEP','PTON','PYPL','QCOM','REGN','ROST','SBUX','SGEN','SIRI','SNPS','SPLK','SWKS','TCOM','TEAM','TMUS',\n",
        "                 'TSLA','TXN','VRSK','VRSN','VRTX','WBA','WDAY','XEL','XLNX','ZM'],\"%d-01-01\" % start_year,today.strftime(\"%Y-%m-%d\"))[\"Adj Close\"] \n",
        "\n",
        "prices.index=pd.DatetimeIndex(prices.index).to_period('D') # this is to make sure the index is properly time aware\n",
        "prices"
      ],
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          "text": [
            "Installing yfinance and getting data...\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.27.1 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "[*********************100%***********************]  101 of 101 completed\n"
          ]
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              "      <td>20.570000</td>\n",
              "      <td>179.898438</td>\n",
              "      <td>...</td>\n",
              "      <td>66.991997</td>\n",
              "      <td>86.668610</td>\n",
              "      <td>107.981079</td>\n",
              "      <td>151.399994</td>\n",
              "      <td>175.850006</td>\n",
              "      <td>61.947548</td>\n",
              "      <td>163.500000</td>\n",
              "      <td>44.552437</td>\n",
              "      <td>86.865608</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-28</th>\n",
              "      <td>165.119995</td>\n",
              "      <td>467.679993</td>\n",
              "      <td>160.289993</td>\n",
              "      <td>204.440002</td>\n",
              "      <td>220.229996</td>\n",
              "      <td>90.650002</td>\n",
              "      <td>511.459991</td>\n",
              "      <td>134.199997</td>\n",
              "      <td>123.339996</td>\n",
              "      <td>226.479996</td>\n",
              "      <td>...</td>\n",
              "      <td>870.429993</td>\n",
              "      <td>169.990005</td>\n",
              "      <td>177.339996</td>\n",
              "      <td>213.720001</td>\n",
              "      <td>230.020004</td>\n",
              "      <td>46.090000</td>\n",
              "      <td>229.050003</td>\n",
              "      <td>67.330002</td>\n",
              "      <td>NaN</td>\n",
              "      <td>132.600006</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-03-01</th>\n",
              "      <td>163.199997</td>\n",
              "      <td>466.679993</td>\n",
              "      <td>156.949997</td>\n",
              "      <td>202.309998</td>\n",
              "      <td>214.000000</td>\n",
              "      <td>90.209999</td>\n",
              "      <td>500.970001</td>\n",
              "      <td>129.610001</td>\n",
              "      <td>113.830002</td>\n",
              "      <td>225.210007</td>\n",
              "      <td>...</td>\n",
              "      <td>864.369995</td>\n",
              "      <td>167.289993</td>\n",
              "      <td>179.360001</td>\n",
              "      <td>216.039993</td>\n",
              "      <td>230.690002</td>\n",
              "      <td>45.009998</td>\n",
              "      <td>240.330002</td>\n",
              "      <td>66.510002</td>\n",
              "      <td>NaN</td>\n",
              "      <td>122.779999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-03-02</th>\n",
              "      <td>166.559998</td>\n",
              "      <td>471.179993</td>\n",
              "      <td>159.820007</td>\n",
              "      <td>206.289993</td>\n",
              "      <td>216.509995</td>\n",
              "      <td>91.239998</td>\n",
              "      <td>496.140015</td>\n",
              "      <td>133.179993</td>\n",
              "      <td>118.279999</td>\n",
              "      <td>228.589996</td>\n",
              "      <td>...</td>\n",
              "      <td>879.890015</td>\n",
              "      <td>170.100006</td>\n",
              "      <td>181.729996</td>\n",
              "      <td>217.850006</td>\n",
              "      <td>234.110001</td>\n",
              "      <td>46.150002</td>\n",
              "      <td>248.389999</td>\n",
              "      <td>67.559998</td>\n",
              "      <td>NaN</td>\n",
              "      <td>121.610001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-03-03</th>\n",
              "      <td>166.229996</td>\n",
              "      <td>459.079987</td>\n",
              "      <td>159.279999</td>\n",
              "      <td>204.699997</td>\n",
              "      <td>210.000000</td>\n",
              "      <td>93.980003</td>\n",
              "      <td>477.450012</td>\n",
              "      <td>130.639999</td>\n",
              "      <td>111.980003</td>\n",
              "      <td>232.639999</td>\n",
              "      <td>...</td>\n",
              "      <td>839.289978</td>\n",
              "      <td>171.000000</td>\n",
              "      <td>182.679993</td>\n",
              "      <td>218.729996</td>\n",
              "      <td>235.690002</td>\n",
              "      <td>46.720001</td>\n",
              "      <td>245.369995</td>\n",
              "      <td>69.129997</td>\n",
              "      <td>NaN</td>\n",
              "      <td>113.110001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-03-04</th>\n",
              "      <td>163.169998</td>\n",
              "      <td>452.130005</td>\n",
              "      <td>156.850006</td>\n",
              "      <td>208.460007</td>\n",
              "      <td>207.660004</td>\n",
              "      <td>96.330002</td>\n",
              "      <td>464.480011</td>\n",
              "      <td>125.739998</td>\n",
              "      <td>108.410004</td>\n",
              "      <td>232.910004</td>\n",
              "      <td>...</td>\n",
              "      <td>838.289978</td>\n",
              "      <td>169.979996</td>\n",
              "      <td>187.699997</td>\n",
              "      <td>217.869995</td>\n",
              "      <td>238.660004</td>\n",
              "      <td>47.720001</td>\n",
              "      <td>240.210007</td>\n",
              "      <td>71.260002</td>\n",
              "      <td>NaN</td>\n",
              "      <td>108.940002</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>801 rows × 101 columns</p>\n",
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            ],
            "text/plain": [
              "                  AAPL        ADBE         ADI         ADP        ADSK  \\\n",
              "Date                                                                     \n",
              "2018-12-31         NaN         NaN         NaN         NaN         NaN   \n",
              "2019-01-02   38.277531  224.570007   80.739853  122.168961  128.960007   \n",
              "2019-01-03   34.464802  215.699997   75.862755  118.479683  121.849998   \n",
              "2019-01-04   35.936077  226.190002   77.704597  123.201614  128.279999   \n",
              "2019-01-07   35.856094  229.259995   78.193245  122.535088  132.720001   \n",
              "...                ...         ...         ...         ...         ...   \n",
              "2022-02-28  165.119995  467.679993  160.289993  204.440002  220.229996   \n",
              "2022-03-01  163.199997  466.679993  156.949997  202.309998  214.000000   \n",
              "2022-03-02  166.559998  471.179993  159.820007  206.289993  216.509995   \n",
              "2022-03-03  166.229996  459.079987  159.279999  204.699997  210.000000   \n",
              "2022-03-04  163.169998  452.130005  156.850006  208.460007  207.660004   \n",
              "\n",
              "                  AEP        ALGN        AMAT         AMD        AMGN  ...  \\\n",
              "Date                                                                   ...   \n",
              "2018-12-31        NaN         NaN         NaN         NaN         NaN  ...   \n",
              "2019-01-02  65.485153  202.119995   32.152931   18.830000  174.294479  ...   \n",
              "2019-01-03  65.332497  184.779999   30.289837   17.049999  171.642395  ...   \n",
              "2019-01-04  65.934044  186.710007   32.364216   19.000000  177.509720  ...   \n",
              "2019-01-07  65.565941  189.919998   32.940434   20.570000  179.898438  ...   \n",
              "...               ...         ...         ...         ...         ...  ...   \n",
              "2022-02-28  90.650002  511.459991  134.199997  123.339996  226.479996  ...   \n",
              "2022-03-01  90.209999  500.970001  129.610001  113.830002  225.210007  ...   \n",
              "2022-03-02  91.239998  496.140015  133.179993  118.279999  228.589996  ...   \n",
              "2022-03-03  93.980003  477.450012  130.639999  111.980003  232.639999  ...   \n",
              "2022-03-04  96.330002  464.480011  125.739998  108.410004  232.910004  ...   \n",
              "\n",
              "                  TSLA         TXN        VRSK        VRSN        VRTX  \\\n",
              "Date                                                                     \n",
              "2018-12-31         NaN         NaN         NaN         NaN         NaN   \n",
              "2019-01-02   62.023998   86.622742  106.568657  147.759995  164.080002   \n",
              "2019-01-03   60.071999   81.514343  103.312256  142.589996  163.729996   \n",
              "2019-01-04   63.537998   85.201195  107.873192  148.970001  172.699997   \n",
              "2019-01-07   66.991997   86.668610  107.981079  151.399994  175.850006   \n",
              "...                ...         ...         ...         ...         ...   \n",
              "2022-02-28  870.429993  169.990005  177.339996  213.720001  230.020004   \n",
              "2022-03-01  864.369995  167.289993  179.360001  216.039993  230.690002   \n",
              "2022-03-02  879.890015  170.100006  181.729996  217.850006  234.110001   \n",
              "2022-03-03  839.289978  171.000000  182.679993  218.729996  235.690002   \n",
              "2022-03-04  838.289978  169.979996  187.699997  217.869995  238.660004   \n",
              "\n",
              "                  WBA        WDAY        XEL       XLNX          ZM  \n",
              "Date                                                                 \n",
              "2018-12-31        NaN         NaN        NaN        NaN         NaN  \n",
              "2019-01-02  60.238846  159.740005  44.487858  84.049446         NaN  \n",
              "2019-01-03  59.610237  154.020004  44.312557  80.884888         NaN  \n",
              "2019-01-04  61.593418  163.350006  44.746178  84.630096         NaN  \n",
              "2019-01-07  61.947548  163.500000  44.552437  86.865608         NaN  \n",
              "...               ...         ...        ...        ...         ...  \n",
              "2022-02-28  46.090000  229.050003  67.330002        NaN  132.600006  \n",
              "2022-03-01  45.009998  240.330002  66.510002        NaN  122.779999  \n",
              "2022-03-02  46.150002  248.389999  67.559998        NaN  121.610001  \n",
              "2022-03-03  46.720001  245.369995  69.129997        NaN  113.110001  \n",
              "2022-03-04  47.720001  240.210007  71.260002        NaN  108.940002  \n",
              "\n",
              "[801 rows x 101 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# make returns\n",
        "returns=pd.DataFrame({ticker:prices[ticker]/prices[ticker].shift()*1e2-1e2 for ticker in list(prices)})\n",
        "returns"
      ],
      "metadata": {
        "id": "jHpRMg5DpSkS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 664
        },
        "outputId": "85997d37-80e7-4997-a77d-fe8fa3c54c76"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>-5.897295</td>\n",
              "      <td>-3.055684</td>\n",
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              "      <td>-0.213314</td>\n",
              "      <td>-1.043527</td>\n",
              "      <td>-3.580819</td>\n",
              "      <td>-0.394041</td>\n",
              "      <td>-3.765115</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-04</th>\n",
              "      <td>4.268921</td>\n",
              "      <td>4.863239</td>\n",
              "      <td>2.427862</td>\n",
              "      <td>3.985436</td>\n",
              "      <td>5.276980</td>\n",
              "      <td>0.920747</td>\n",
              "      <td>1.044490</td>\n",
              "      <td>6.848432</td>\n",
              "      <td>11.436955</td>\n",
              "      <td>3.418342</td>\n",
              "      <td>...</td>\n",
              "      <td>5.769742</td>\n",
              "      <td>4.522948</td>\n",
              "      <td>4.414710</td>\n",
              "      <td>4.474371</td>\n",
              "      <td>5.478533</td>\n",
              "      <td>3.326913</td>\n",
              "      <td>6.057656</td>\n",
              "      <td>0.978550</td>\n",
              "      <td>4.630295</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-07</th>\n",
              "      <td>-0.222570</td>\n",
              "      <td>1.357262</td>\n",
              "      <td>0.628853</td>\n",
              "      <td>-0.541005</td>\n",
              "      <td>3.461181</td>\n",
              "      <td>-0.558290</td>\n",
              "      <td>1.719239</td>\n",
              "      <td>1.780416</td>\n",
              "      <td>8.263156</td>\n",
              "      <td>1.345683</td>\n",
              "      <td>...</td>\n",
              "      <td>5.436115</td>\n",
              "      <td>1.722294</td>\n",
              "      <td>0.100013</td>\n",
              "      <td>1.631196</td>\n",
              "      <td>1.823978</td>\n",
              "      <td>0.574947</td>\n",
              "      <td>0.091824</td>\n",
              "      <td>-0.432977</td>\n",
              "      <td>2.641509</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-28</th>\n",
              "      <td>0.163779</td>\n",
              "      <td>0.459678</td>\n",
              "      <td>-1.128795</td>\n",
              "      <td>0.039147</td>\n",
              "      <td>0.277753</td>\n",
              "      <td>1.330206</td>\n",
              "      <td>-0.214610</td>\n",
              "      <td>-1.119956</td>\n",
              "      <td>1.883363</td>\n",
              "      <td>-0.242260</td>\n",
              "      <td>...</td>\n",
              "      <td>7.477743</td>\n",
              "      <td>-0.485893</td>\n",
              "      <td>-1.225352</td>\n",
              "      <td>-0.219432</td>\n",
              "      <td>-0.121580</td>\n",
              "      <td>-0.238097</td>\n",
              "      <td>1.696047</td>\n",
              "      <td>0.148741</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.809134</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-03-01</th>\n",
              "      <td>-1.162790</td>\n",
              "      <td>-0.213821</td>\n",
              "      <td>-2.083721</td>\n",
              "      <td>-1.041873</td>\n",
              "      <td>-2.828859</td>\n",
              "      <td>-0.485386</td>\n",
              "      <td>-2.050989</td>\n",
              "      <td>-3.420266</td>\n",
              "      <td>-7.710390</td>\n",
              "      <td>-0.560751</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.696207</td>\n",
              "      <td>-1.588336</td>\n",
              "      <td>1.139057</td>\n",
              "      <td>1.085529</td>\n",
              "      <td>0.291278</td>\n",
              "      <td>-2.343245</td>\n",
              "      <td>4.924688</td>\n",
              "      <td>-1.217882</td>\n",
              "      <td>NaN</td>\n",
              "      <td>-7.405737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-03-02</th>\n",
              "      <td>2.058824</td>\n",
              "      <td>0.964258</td>\n",
              "      <td>1.828614</td>\n",
              "      <td>1.967276</td>\n",
              "      <td>1.172895</td>\n",
              "      <td>1.141779</td>\n",
              "      <td>-0.964127</td>\n",
              "      <td>2.754411</td>\n",
              "      <td>3.909336</td>\n",
              "      <td>1.500817</td>\n",
              "      <td>...</td>\n",
              "      <td>1.795530</td>\n",
              "      <td>1.679726</td>\n",
              "      <td>1.321362</td>\n",
              "      <td>0.837814</td>\n",
              "      <td>1.482508</td>\n",
              "      <td>2.532778</td>\n",
              "      <td>3.353721</td>\n",
              "      <td>1.578703</td>\n",
              "      <td>NaN</td>\n",
              "      <td>-0.952922</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-03-03</th>\n",
              "      <td>-0.198128</td>\n",
              "      <td>-2.568022</td>\n",
              "      <td>-0.337885</td>\n",
              "      <td>-0.770758</td>\n",
              "      <td>-3.006787</td>\n",
              "      <td>3.003075</td>\n",
              "      <td>-3.767082</td>\n",
              "      <td>-1.907188</td>\n",
              "      <td>-5.326340</td>\n",
              "      <td>1.771732</td>\n",
              "      <td>...</td>\n",
              "      <td>-4.614217</td>\n",
              "      <td>0.529097</td>\n",
              "      <td>0.522752</td>\n",
              "      <td>0.403943</td>\n",
              "      <td>0.674897</td>\n",
              "      <td>1.235102</td>\n",
              "      <td>-1.215832</td>\n",
              "      <td>2.323860</td>\n",
              "      <td>NaN</td>\n",
              "      <td>-6.989557</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-03-04</th>\n",
              "      <td>-1.840822</td>\n",
              "      <td>-1.513893</td>\n",
              "      <td>-1.525611</td>\n",
              "      <td>1.836839</td>\n",
              "      <td>-1.114284</td>\n",
              "      <td>2.500530</td>\n",
              "      <td>-2.716515</td>\n",
              "      <td>-3.750767</td>\n",
              "      <td>-3.188069</td>\n",
              "      <td>0.116061</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.119148</td>\n",
              "      <td>-0.596494</td>\n",
              "      <td>2.747977</td>\n",
              "      <td>-0.393179</td>\n",
              "      <td>1.260130</td>\n",
              "      <td>2.140411</td>\n",
              "      <td>-2.102942</td>\n",
              "      <td>3.081159</td>\n",
              "      <td>NaN</td>\n",
              "      <td>-3.686675</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>801 rows × 101 columns</p>\n",
              "</div>\n",
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            ],
            "text/plain": [
              "                AAPL      ADBE       ADI       ADP      ADSK       AEP  \\\n",
              "Date                                                                     \n",
              "2018-12-31       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "2019-01-02       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "2019-01-03 -9.960749 -3.949775 -6.040509 -3.019816 -5.513344 -0.233116   \n",
              "2019-01-04  4.268921  4.863239  2.427862  3.985436  5.276980  0.920747   \n",
              "2019-01-07 -0.222570  1.357262  0.628853 -0.541005  3.461181 -0.558290   \n",
              "...              ...       ...       ...       ...       ...       ...   \n",
              "2022-02-28  0.163779  0.459678 -1.128795  0.039147  0.277753  1.330206   \n",
              "2022-03-01 -1.162790 -0.213821 -2.083721 -1.041873 -2.828859 -0.485386   \n",
              "2022-03-02  2.058824  0.964258  1.828614  1.967276  1.172895  1.141779   \n",
              "2022-03-03 -0.198128 -2.568022 -0.337885 -0.770758 -3.006787  3.003075   \n",
              "2022-03-04 -1.840822 -1.513893 -1.525611  1.836839 -1.114284  2.500530   \n",
              "\n",
              "                ALGN      AMAT        AMD      AMGN  ...      TSLA       TXN  \\\n",
              "Date                                                 ...                       \n",
              "2018-12-31       NaN       NaN        NaN       NaN  ...       NaN       NaN   \n",
              "2019-01-02       NaN       NaN        NaN       NaN  ...       NaN       NaN   \n",
              "2019-01-03 -8.579060 -5.794477  -9.453004 -1.521611  ... -3.147168 -5.897295   \n",
              "2019-01-04  1.044490  6.848432  11.436955  3.418342  ...  5.769742  4.522948   \n",
              "2019-01-07  1.719239  1.780416   8.263156  1.345683  ...  5.436115  1.722294   \n",
              "...              ...       ...        ...       ...  ...       ...       ...   \n",
              "2022-02-28 -0.214610 -1.119956   1.883363 -0.242260  ...  7.477743 -0.485893   \n",
              "2022-03-01 -2.050989 -3.420266  -7.710390 -0.560751  ... -0.696207 -1.588336   \n",
              "2022-03-02 -0.964127  2.754411   3.909336  1.500817  ...  1.795530  1.679726   \n",
              "2022-03-03 -3.767082 -1.907188  -5.326340  1.771732  ... -4.614217  0.529097   \n",
              "2022-03-04 -2.716515 -3.750767  -3.188069  0.116061  ... -0.119148 -0.596494   \n",
              "\n",
              "                VRSK      VRSN      VRTX       WBA      WDAY       XEL  \\\n",
              "Date                                                                     \n",
              "2018-12-31       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "2019-01-02       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "2019-01-03 -3.055684 -3.498916 -0.213314 -1.043527 -3.580819 -0.394041   \n",
              "2019-01-04  4.414710  4.474371  5.478533  3.326913  6.057656  0.978550   \n",
              "2019-01-07  0.100013  1.631196  1.823978  0.574947  0.091824 -0.432977   \n",
              "...              ...       ...       ...       ...       ...       ...   \n",
              "2022-02-28 -1.225352 -0.219432 -0.121580 -0.238097  1.696047  0.148741   \n",
              "2022-03-01  1.139057  1.085529  0.291278 -2.343245  4.924688 -1.217882   \n",
              "2022-03-02  1.321362  0.837814  1.482508  2.532778  3.353721  1.578703   \n",
              "2022-03-03  0.522752  0.403943  0.674897  1.235102 -1.215832  2.323860   \n",
              "2022-03-04  2.747977 -0.393179  1.260130  2.140411 -2.102942  3.081159   \n",
              "\n",
              "                XLNX        ZM  \n",
              "Date                            \n",
              "2018-12-31       NaN       NaN  \n",
              "2019-01-02       NaN       NaN  \n",
              "2019-01-03 -3.765115       NaN  \n",
              "2019-01-04  4.630295       NaN  \n",
              "2019-01-07  2.641509       NaN  \n",
              "...              ...       ...  \n",
              "2022-02-28       NaN  5.809134  \n",
              "2022-03-01       NaN -7.405737  \n",
              "2022-03-02       NaN -0.952922  \n",
              "2022-03-03       NaN -6.989557  \n",
              "2022-03-04       NaN -3.686675  \n",
              "\n",
              "[801 rows x 101 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# compute correlation matrix\n",
        "rho=returns.corr(method='pearson',min_periods=10)\n",
        "display(rho)\n",
        "\n",
        "for row in range(rho.shape[0]):\n",
        "    for column in range(row,rho.shape[0]):\n",
        "        rho.iloc[row,column]=np.nan # to get rid of the diagonal and upper right triangle\n",
        "\n",
        "rho[\"LeftTicker\"]=rho.index\n",
        "rhov=rho.melt(id_vars='LeftTicker',var_name='RightTicker',value_name='Correlation').dropna()\n",
        "rhov=rhov[(rhov[\"LeftTicker\"]!=\"Ticker\")&(rhov[\"RightTicker\"]!=\"Ticker\")]\n",
        "\n",
        "# make a histogram\n",
        "from matplotlib import pyplot as pl ; GoldenRatio=(1e0+np.sqrt(5e0))/2e0\n",
        "figure,plot=pl.subplots(figsize=(10*GoldenRatio,10))\n",
        "rhov[\"Correlation\"].hist(ax=plot,bins=np.linspace(rhov[\"Correlation\"].min(),rhov[\"Correlation\"].max(),101))\n",
        "plot.grid(None)\n",
        "plot.set_title(\"Correlation of NASDAQ-100 Member Returns for 2021-12-21 Universe\",fontsize=22)\n",
        "plot.set_xlabel(\"Information Coefficient, $R$\",fontsize=14)\n",
        "plot.set_ylabel(\"Frequency\",fontsize=14)\n",
        "plot.axvline(alpha=0.25)\n",
        "\n",
        "# collapse the dataframe\n",
        "rhov.index=rhov[\"LeftTicker\"]+\",\"+rhov[\"RightTicker\"]\n",
        "rhov.drop([\"LeftTicker\",\"RightTicker\"],axis=1,inplace=True)\n",
        "rhov.sort_values(\"Correlation\",inplace=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "u5NEUJsVpdTr",
        "outputId": "766a475a-28e1-4905-d93f-bdc88d0da59e"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>AAPL</th>\n",
              "      <th>ADBE</th>\n",
              "      <th>ADI</th>\n",
              "      <th>ADP</th>\n",
              "      <th>ADSK</th>\n",
              "      <th>AEP</th>\n",
              "      <th>ALGN</th>\n",
              "      <th>AMAT</th>\n",
              "      <th>AMD</th>\n",
              "      <th>AMGN</th>\n",
              "      <th>...</th>\n",
              "      <th>TSLA</th>\n",
              "      <th>TXN</th>\n",
              "      <th>VRSK</th>\n",
              "      <th>VRSN</th>\n",
              "      <th>VRTX</th>\n",
              "      <th>WBA</th>\n",
              "      <th>WDAY</th>\n",
              "      <th>XEL</th>\n",
              "      <th>XLNX</th>\n",
              "      <th>ZM</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>AAPL</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.685102</td>\n",
              "      <td>0.611433</td>\n",
              "      <td>0.561655</td>\n",
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              "      <td>0.346973</td>\n",
              "      <td>0.460719</td>\n",
              "      <td>0.603677</td>\n",
              "      <td>0.571382</td>\n",
              "      <td>0.484952</td>\n",
              "      <td>...</td>\n",
              "      <td>0.449771</td>\n",
              "      <td>0.649378</td>\n",
              "      <td>0.572160</td>\n",
              "      <td>0.640433</td>\n",
              "      <td>0.433774</td>\n",
              "      <td>0.325726</td>\n",
              "      <td>0.504055</td>\n",
              "      <td>0.418197</td>\n",
              "      <td>0.514147</td>\n",
              "      <td>0.182426</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ADBE</th>\n",
              "      <td>0.685102</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.630942</td>\n",
              "      <td>0.561388</td>\n",
              "      <td>0.715117</td>\n",
              "      <td>0.292083</td>\n",
              "      <td>0.441020</td>\n",
              "      <td>0.596272</td>\n",
              "      <td>0.573913</td>\n",
              "      <td>0.449843</td>\n",
              "      <td>...</td>\n",
              "      <td>0.448653</td>\n",
              "      <td>0.639030</td>\n",
              "      <td>0.590892</td>\n",
              "      <td>0.708384</td>\n",
              "      <td>0.469874</td>\n",
              "      <td>0.225974</td>\n",
              "      <td>0.674681</td>\n",
              "      <td>0.374323</td>\n",
              "      <td>0.555905</td>\n",
              "      <td>0.314607</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ADI</th>\n",
              "      <td>0.611433</td>\n",
              "      <td>0.630942</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.576086</td>\n",
              "      <td>0.621553</td>\n",
              "      <td>0.271177</td>\n",
              "      <td>0.516586</td>\n",
              "      <td>0.782752</td>\n",
              "      <td>0.578912</td>\n",
              "      <td>0.443938</td>\n",
              "      <td>...</td>\n",
              "      <td>0.414760</td>\n",
              "      <td>0.854331</td>\n",
              "      <td>0.548977</td>\n",
              "      <td>0.622047</td>\n",
              "      <td>0.393441</td>\n",
              "      <td>0.323122</td>\n",
              "      <td>0.508496</td>\n",
              "      <td>0.367021</td>\n",
              "      <td>0.680510</td>\n",
              "      <td>0.095754</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ADP</th>\n",
              "      <td>0.561655</td>\n",
              "      <td>0.561388</td>\n",
              "      <td>0.576086</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.562361</td>\n",
              "      <td>0.529337</td>\n",
              "      <td>0.518325</td>\n",
              "      <td>0.552008</td>\n",
              "      <td>0.415848</td>\n",
              "      <td>0.510301</td>\n",
              "      <td>...</td>\n",
              "      <td>0.306810</td>\n",
              "      <td>0.611423</td>\n",
              "      <td>0.657725</td>\n",
              "      <td>0.639255</td>\n",
              "      <td>0.419964</td>\n",
              "      <td>0.428074</td>\n",
              "      <td>0.484024</td>\n",
              "      <td>0.573197</td>\n",
              "      <td>0.427387</td>\n",
              "      <td>-0.013586</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ADSK</th>\n",
              "      <td>0.597637</td>\n",
              "      <td>0.715117</td>\n",
              "      <td>0.621553</td>\n",
              "      <td>0.562361</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.270305</td>\n",
              "      <td>0.521845</td>\n",
              "      <td>0.614007</td>\n",
              "      <td>0.534429</td>\n",
              "      <td>0.375687</td>\n",
              "      <td>...</td>\n",
              "      <td>0.418829</td>\n",
              "      <td>0.625648</td>\n",
              "      <td>0.506688</td>\n",
              "      <td>0.589527</td>\n",
              "      <td>0.406446</td>\n",
              "      <td>0.316128</td>\n",
              "      <td>0.618453</td>\n",
              "      <td>0.325281</td>\n",
              "      <td>0.533030</td>\n",
              "      <td>0.257155</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>WBA</th>\n",
              "      <td>0.325726</td>\n",
              "      <td>0.225974</td>\n",
              "      <td>0.323122</td>\n",
              "      <td>0.428074</td>\n",
              "      <td>0.316128</td>\n",
              "      <td>0.358979</td>\n",
              "      <td>0.284978</td>\n",
              "      <td>0.356753</td>\n",
              "      <td>0.235462</td>\n",
              "      <td>0.388369</td>\n",
              "      <td>...</td>\n",
              "      <td>0.131474</td>\n",
              "      <td>0.385053</td>\n",
              "      <td>0.298094</td>\n",
              "      <td>0.283169</td>\n",
              "      <td>0.250362</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.145705</td>\n",
              "      <td>0.314571</td>\n",
              "      <td>0.274535</td>\n",
              "      <td>-0.121609</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>WDAY</th>\n",
              "      <td>0.504055</td>\n",
              "      <td>0.674681</td>\n",
              "      <td>0.508496</td>\n",
              "      <td>0.484024</td>\n",
              "      <td>0.618453</td>\n",
              "      <td>0.219432</td>\n",
              "      <td>0.399384</td>\n",
              "      <td>0.513165</td>\n",
              "      <td>0.479300</td>\n",
              "      <td>0.282239</td>\n",
              "      <td>...</td>\n",
              "      <td>0.395344</td>\n",
              "      <td>0.499629</td>\n",
              "      <td>0.475283</td>\n",
              "      <td>0.541389</td>\n",
              "      <td>0.323290</td>\n",
              "      <td>0.145705</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.264707</td>\n",
              "      <td>0.448530</td>\n",
              "      <td>0.274391</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>XEL</th>\n",
              "      <td>0.418197</td>\n",
              "      <td>0.374323</td>\n",
              "      <td>0.367021</td>\n",
              "      <td>0.573197</td>\n",
              "      <td>0.325281</td>\n",
              "      <td>0.836399</td>\n",
              "      <td>0.310283</td>\n",
              "      <td>0.324480</td>\n",
              "      <td>0.234094</td>\n",
              "      <td>0.493010</td>\n",
              "      <td>...</td>\n",
              "      <td>0.136808</td>\n",
              "      <td>0.393017</td>\n",
              "      <td>0.630608</td>\n",
              "      <td>0.528959</td>\n",
              "      <td>0.361303</td>\n",
              "      <td>0.314571</td>\n",
              "      <td>0.264707</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.200750</td>\n",
              "      <td>-0.045926</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>XLNX</th>\n",
              "      <td>0.514147</td>\n",
              "      <td>0.555905</td>\n",
              "      <td>0.680510</td>\n",
              "      <td>0.427387</td>\n",
              "      <td>0.533030</td>\n",
              "      <td>0.153486</td>\n",
              "      <td>0.412918</td>\n",
              "      <td>0.669205</td>\n",
              "      <td>0.644691</td>\n",
              "      <td>0.301363</td>\n",
              "      <td>...</td>\n",
              "      <td>0.367316</td>\n",
              "      <td>0.716817</td>\n",
              "      <td>0.424289</td>\n",
              "      <td>0.509730</td>\n",
              "      <td>0.329968</td>\n",
              "      <td>0.274535</td>\n",
              "      <td>0.448530</td>\n",
              "      <td>0.200750</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.139387</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ZM</th>\n",
              "      <td>0.182426</td>\n",
              "      <td>0.314607</td>\n",
              "      <td>0.095754</td>\n",
              "      <td>-0.013586</td>\n",
              "      <td>0.257155</td>\n",
              "      <td>-0.061993</td>\n",
              "      <td>0.095464</td>\n",
              "      <td>0.131371</td>\n",
              "      <td>0.261289</td>\n",
              "      <td>-0.000588</td>\n",
              "      <td>...</td>\n",
              "      <td>0.252105</td>\n",
              "      <td>0.107699</td>\n",
              "      <td>0.039930</td>\n",
              "      <td>0.146862</td>\n",
              "      <td>0.043624</td>\n",
              "      <td>-0.121609</td>\n",
              "      <td>0.274391</td>\n",
              "      <td>-0.045926</td>\n",
              "      <td>0.139387</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>101 rows × 101 columns</p>\n",
              "</div>\n",
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            "text/plain": [
              "          AAPL      ADBE       ADI       ADP      ADSK       AEP      ALGN  \\\n",
              "AAPL  1.000000  0.685102  0.611433  0.561655  0.597637  0.346973  0.460719   \n",
              "ADBE  0.685102  1.000000  0.630942  0.561388  0.715117  0.292083  0.441020   \n",
              "ADI   0.611433  0.630942  1.000000  0.576086  0.621553  0.271177  0.516586   \n",
              "ADP   0.561655  0.561388  0.576086  1.000000  0.562361  0.529337  0.518325   \n",
              "ADSK  0.597637  0.715117  0.621553  0.562361  1.000000  0.270305  0.521845   \n",
              "...        ...       ...       ...       ...       ...       ...       ...   \n",
              "WBA   0.325726  0.225974  0.323122  0.428074  0.316128  0.358979  0.284978   \n",
              "WDAY  0.504055  0.674681  0.508496  0.484024  0.618453  0.219432  0.399384   \n",
              "XEL   0.418197  0.374323  0.367021  0.573197  0.325281  0.836399  0.310283   \n",
              "XLNX  0.514147  0.555905  0.680510  0.427387  0.533030  0.153486  0.412918   \n",
              "ZM    0.182426  0.314607  0.095754 -0.013586  0.257155 -0.061993  0.095464   \n",
              "\n",
              "          AMAT       AMD      AMGN  ...      TSLA       TXN      VRSK  \\\n",
              "AAPL  0.603677  0.571382  0.484952  ...  0.449771  0.649378  0.572160   \n",
              "ADBE  0.596272  0.573913  0.449843  ...  0.448653  0.639030  0.590892   \n",
              "ADI   0.782752  0.578912  0.443938  ...  0.414760  0.854331  0.548977   \n",
              "ADP   0.552008  0.415848  0.510301  ...  0.306810  0.611423  0.657725   \n",
              "ADSK  0.614007  0.534429  0.375687  ...  0.418829  0.625648  0.506688   \n",
              "...        ...       ...       ...  ...       ...       ...       ...   \n",
              "WBA   0.356753  0.235462  0.388369  ...  0.131474  0.385053  0.298094   \n",
              "WDAY  0.513165  0.479300  0.282239  ...  0.395344  0.499629  0.475283   \n",
              "XEL   0.324480  0.234094  0.493010  ...  0.136808  0.393017  0.630608   \n",
              "XLNX  0.669205  0.644691  0.301363  ...  0.367316  0.716817  0.424289   \n",
              "ZM    0.131371  0.261289 -0.000588  ...  0.252105  0.107699  0.039930   \n",
              "\n",
              "          VRSN      VRTX       WBA      WDAY       XEL      XLNX        ZM  \n",
              "AAPL  0.640433  0.433774  0.325726  0.504055  0.418197  0.514147  0.182426  \n",
              "ADBE  0.708384  0.469874  0.225974  0.674681  0.374323  0.555905  0.314607  \n",
              "ADI   0.622047  0.393441  0.323122  0.508496  0.367021  0.680510  0.095754  \n",
              "ADP   0.639255  0.419964  0.428074  0.484024  0.573197  0.427387 -0.013586  \n",
              "ADSK  0.589527  0.406446  0.316128  0.618453  0.325281  0.533030  0.257155  \n",
              "...        ...       ...       ...       ...       ...       ...       ...  \n",
              "WBA   0.283169  0.250362  1.000000  0.145705  0.314571  0.274535 -0.121609  \n",
              "WDAY  0.541389  0.323290  0.145705  1.000000  0.264707  0.448530  0.274391  \n",
              "XEL   0.528959  0.361303  0.314571  0.264707  1.000000  0.200750 -0.045926  \n",
              "XLNX  0.509730  0.329968  0.274535  0.448530  0.200750  1.000000  0.139387  \n",
              "ZM    0.146862  0.043624 -0.121609  0.274391 -0.045926  0.139387  1.000000  \n",
              "\n",
              "[101 rows x 101 columns]"
            ]
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\n",
            "text/plain": [
              "<Figure size 1164.98x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# select a suitable data pair\n",
        "np.random.seed(123456) # set the seed to guarantee reproducability\n",
        "pair=np.random.choice(rhov.index[(rhov[\"Correlation\"]>=0.09e0)&(rhov[\"Correlation\"]<=0.11e0)])\n",
        "x_name,y_name=pair.split(\",\")\n",
        "print(\"Processing (%s) with correlation %g.\" % (pair,rhov.loc[pair,\"Correlation\"]))\n",
        "data=pd.DataFrame({k:returns[k] for k in pair.split(',')}).dropna()\n",
        "\n",
        "# linear regression\n",
        "from statsmodels.formula.api import ols\n",
        "from statsmodels.sandbox.regression.predstd import wls_prediction_std\n",
        "alpha=0.05 # set alpha_critical to 5%\n",
        "fit=ols(\"%s ~ %s\" % (y_name,x_name),data).fit() # do OLS regression\n",
        "data['model']=fit.fittedvalues # get the fit\n",
        "print(fit.summary()) # print the regression summary\n",
        "\n",
        "x,y,yhat=tuple(map(lambda c:data[c].tolist(),(x_name,y_name,\"model\")))\n",
        "sig,crl,cru,=wls_prediction_std(fit,alpha=alpha) # get the confidence regions with given alpha\n",
        "x,y,yhat,crl,cru=tuple(zip(*list(sorted(zip(x,y,yhat,crl,cru),key=lambda a:a[0])))) # sort all values by x\n",
        "\n",
        "# make scatter plot\n",
        "figure,plot=pl.subplots(figsize=(10*GoldenRatio,10))\n",
        "plot.plot(x,y,'bo',label='Data')\n",
        "plot.plot(x,yhat,'r-',label='Regression Line')\n",
        "plot.fill_between(x,crl,cru,alpha=0.2,label='%.0f%% Confidence Region' % (1e2-1e2*alpha))\n",
        "plot.set_title(\"Correlation of Daily Returns for (%s)\" % pair,fontsize=22)\n",
        "plot.axhline(alpha=0.25)\n",
        "plot.axvline(alpha=0.25)\n",
        "plot.set_xlabel(\"%s Return (%%)\" % x_name,fontsize=14)\n",
        "plot.set_ylabel(\"%s Return (%%)\" % y_name,fontsize=14)\n",
        "plot.legend();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Zog3eHS4D3qx",
        "outputId": "3ec3e9c7-d00e-4091-e4b2-952ca07e270e"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Processing (ZM,INTC) with correlation 0.0907623.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                            OLS Regression Results                            \n",
            "==============================================================================\n",
            "Dep. Variable:                   INTC   R-squared:                       0.008\n",
            "Model:                            OLS   Adj. R-squared:                  0.007\n",
            "Method:                 Least Squares   F-statistic:                     6.005\n",
            "Date:                Mon, 07 Mar 2022   Prob (F-statistic):             0.0145\n",
            "Time:                        17:31:49   Log-Likelihood:                -1693.2\n",
            "No. Observations:                 725   AIC:                             3390.\n",
            "Df Residuals:                     723   BIC:                             3399.\n",
            "Df Model:                           1                                         \n",
            "Covariance Type:            nonrobust                                         \n",
            "==============================================================================\n",
            "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
            "------------------------------------------------------------------------------\n",
            "Intercept      0.0064      0.093      0.069      0.945      -0.176       0.189\n",
            "ZM             0.0532      0.022      2.451      0.014       0.011       0.096\n",
            "==============================================================================\n",
            "Omnibus:                      185.057   Durbin-Watson:                   2.473\n",
            "Prob(Omnibus):                  0.000   Jarque-Bera (JB):             5770.239\n",
            "Skew:                          -0.428   Prob(JB):                         0.00\n",
            "Kurtosis:                      16.794   Cond. No.                         4.29\n",
            "==============================================================================\n",
            "\n",
            "Warnings:\n",
            "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1164.98x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# barrier scan\n",
        "alpha_sd=data[x_name].std()\n",
        "\n",
        "from tqdm.notebook import tqdm\n",
        "trials=np.linspace(0e0,3e0,151)\n",
        "sharpe=pd.DataFrame({\"Barrier\":trials,\"Sharpe\":[np.nan]*trials.shape[0]}).set_index(\"Barrier\")\n",
        "print(\"Varying trade entry barrier over range [%g,%d].\" % (trials[0],trials[-1]))\n",
        "\n",
        "for barrier in tqdm(sharpe.index):\n",
        "    scan=data[[x_name,y_name]].copy() # take a copy of the returns \n",
        "    scan[\"alpha_std\"]=scan[x_name]/alpha_sd\n",
        "    scan.loc[scan.index[0],\"holding\"]=0e0\n",
        "\n",
        "    for i,date in enumerate(scan.index[1:]):\n",
        "        scan.loc[date,\"holding\"]=np.sign(scan.loc[date,\"alpha_std\"]) if abs(scan.loc[date,\"alpha_std\"])>=barrier else scan.loc[scan.index[i],\"holding\"]\n",
        "\n",
        "    scan[\"prior_holding\"]=scan[\"holding\"].shift()\n",
        "    scan[\"pnl\"]=scan[\"prior_holding\"]*scan[y_name]\n",
        "    sharpe.loc[barrier,\"Sharpe\"]=scan[\"pnl\"].mean()/scan[\"pnl\"].std()*np.sqrt(252e0)\n",
        "\n",
        "barrier=sharpe.index[sharpe[\"Sharpe\"].argmax()]\n",
        "\n",
        "figure,plot=pl.subplots(figsize=(10*GoldenRatio,10))\n",
        "sharpe.plot(ax=plot)\n",
        "plot.axhline(alpha=0.25)\n",
        "plot.axvline(alpha=0.25)\n",
        "plot.axvline(barrier,alpha=0.25)\n",
        "plot.set_xlabel(\"Trade Entry Barrier/S.D. of Alpha\",fontsize=14)\n",
        "plot.set_ylabel(\"Sharpe Ratio\",fontsize=14)\n",
        "figure.suptitle(\"Variation of Sharpe Ratio with Trade Entry Barrier\",fontsize=22)\n",
        "plot.get_legend().remove();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 730,
          "referenced_widgets": [
            "811f54eb955041b380a6d1eb59afec30",
            "cb5a52c3d5ec4e629b1c995eb6257660",
            "9a00d0595c324ce699ade7cd08e55db2",
            "75b115fc675c475faf1bec1e12953b34",
            "f2f6aba09ad049afbc968e937b34a206",
            "b6abc8a6de8847caba851955d2558869",
            "1edf87c0f1a04ca191ede436c4960b85",
            "a77505e5faba4cc9acd7c6c4e1b150b5",
            "02d454659f924a78adbe2e38b9bce710",
            "00c0c79a731a4aaea455db72cab3bbd9",
            "7f2aa5bf153b412abe308cf48f0de513"
          ]
        },
        "id": "_RB1grX5G-Jz",
        "outputId": "704cb4fe-f5a7-4d81-bf5a-f4c99a928d36"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Varying trade entry barrier over range [0,3].\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "811f54eb955041b380a6d1eb59afec30",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "  0%|          | 0/151 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1164.98x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# simulate barrier trading with barrier at B sigma of alpha\n",
        "print(\"Simulate barrier trading of %s with entry barrier at ±%g times the s.d. of the alpha, which is %g.\" % (y_name,barrier,alpha_sd))\n",
        "\n",
        "data[\"alpha_std\"]=data[x_name]/alpha_sd\n",
        "data.loc[data.index[0],\"holding\"]=0e0\n",
        "\n",
        "for i,date in enumerate(data.index[1:]): # starts on day #2, data.index[i] is the prior day!\n",
        "    data.loc[date,\"holding\"]=np.sign(data.loc[date,\"alpha_std\"]) if abs(data.loc[date,\"alpha_std\"])>=barrier else data.loc[data.index[i],\"holding\"]\n",
        "\n",
        "data[\"prior_holding\"]=data[\"holding\"].shift()\n",
        "data.loc[data.index[0],\"prior_holding\"]=0e0\n",
        "data[\"trade\"]=data[\"holding\"]-data[\"prior_holding\"]\n",
        "data[\"pnl\"]=data[\"prior_holding\"]*data[y_name]\n",
        "print(\"With zero costs, trading has a Sharpe Ratio of %g.\" % (data[\"pnl\"].mean()/data[\"pnl\"].std()*np.sqrt(252e0)))\n",
        "\n",
        "# make cumulative p/l curve using the log trick\n",
        "data[\"total_pnl\"]=np.exp(np.log(1e0+data[\"pnl\"]/1e2).cumsum())*1e2-1e2\n",
        "plots=list(pl.subplots(figsize=(10*GoldenRatio,10))) # plots[0] is the figure\n",
        "data[\"total_pnl\"].plot(ax=plots[1],label=\"Total P/L\",color=\"C0\",lw=3)\n",
        "plots[1].set_xlabel(None)\n",
        "plots[1].set_ylabel(\"Return (%)\",fontsize=14)\n",
        "plots[1].axhline(alpha=0.25)\n",
        "plots[1].set_ylim(-150,150)\n",
        "\n",
        "# make a second axis\n",
        "plots.append(plots[1].twinx())\n",
        "data[\"holding\"].plot(ax=plots[2],label=\"Holding\",color=\"C1\",alpha=0.6)\n",
        "plots[2].set_ylim(-2,2)\n",
        "plots[2].set_ylabel(\"Holding\",fontsize=14)\n",
        "\n",
        "# decorate figure\n",
        "plots[0].suptitle(\"Cumulative P/L for Barrier Strategy on %s with Zero Transaction Costs\" % y_name,fontsize=22)\n",
        "plots[0].legend(loc=(0.074,0.80),fontsize=14);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        },
        "id": "7N0tzpBKDO05",
        "outputId": "959b16c0-44ec-4b4a-d3c2-68af3c5fd63e"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Simulate barrier trading of INTC with entry barrier at ±0.78 times the s.d. of the alpha, which is 4.28357.\n",
            "With zero costs, trading has a Sharpe Ratio of 0.926627.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1164.98x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "z2PtyTrJ8wh9"
      },
      "execution_count": 6,
      "outputs": []
    }
  ]
}